Earth Observation (EO) mining systems aim at supporting efficient access and exploration of large volumes of image products. In this work, we address the problem of content-based image retrieval via example-based queries from Petabyte-scale EO data archives. To this end, we propose an interactive data mining system that relies on distributing unsupervised ingestion processes onto virtual machine instances in elastic, on-demand computing infrastructures that also support archive-scale content indexing via a "big data" analytics cluster-computing framework.

Aiming at a quantitative understanding of basic aspects of pedestrian dynamics, extensive and high-accuracy measurements of real-life pedestrian trajectories have been performed. A measurement strategy based on Microsoft KinectTM has been used. Specifically, more than 100.000 pedestrians have been tracked while walking along a trafficked corridor at the Eindhoven University of Technology, The Netherlands.

We analyze the dynamics of a two-dimensional system of interacting active dumbbells. We characterize the mean-square displacement, linear response function, and deviation from the equilibrium fluctuation-dissipation theorem as a function of activity strength, packing fraction, and temperature for parameters such that the system is in its homogeneous phase.

The aim of the paper is to analyze the performance of a portfolio of participating life annuities, focusing on the minimum acceptable income level throughout the quantiles of the return distribution. The model, in addition to the necessary consideration of the volatility of financial markets, gives a central role to the impact of the longevity phenomenon.

The purpose of this article is to present a methodology to identify the sources of activity in brain networks from functional magnetic resonance imaging (fMRI) data using the multiset canonical correlation analysis algorithm. The aim is to lay the foundations for a screening marker to be used as indicator of mental diseases. Group analysis blind source separation methods have proved reliable to extract the latent sources underlying the brain activities but currently there is no recognized biomarker for mental disorders.

Recently, synthetic aperture radar interferometry (InSAR) has been recognized as a promising tool to generate high-resolution maps of atmospherical precipitable water vapor temporal changes (Delta PWV) from the propagation delay of radar signal in atmosphere. The relationship between Delta PWV and propagation delay mainly depends on the vertical profiles of temperature and water vapor pressure. In this letter, we present a methodology to study the spatial and temporal variations of the temperature's vertical profile and generate more accurate high-resolution Delta PWV maps by means of InSAR.

Results from direct numerical simulations (DNS) of particle relative dispersion in three-dimensional homogeneous and isotropic turbulence at Reynolds number Re?~300 are presented. We study point-like passive tracers and heavy particles, at Stokes number St=0.6,1 and 5. Particles are emitted from localised sources, in bunches of thousands, periodically in time, allowing an unprecedented statistical accuracy to be reached, with a total number of events for two-point observables of the order of 1011.